The proposed Supervision Levels Scale (SLS) can be applied to provide additional supervision tags as methods are compared on the same test set.
Previous efforts to find discrete scales or categories have focused on identifying easy or hard examples within one datasets, in order to provide insights into methods failure cases (e.g. [1]}, [2]}, [3]}).
Up to our knowledge, there is no previous attempt to provide a discrete scale of the levels of supervision on the same dataset.
We hope that this first attempt can be further utilised and elaborated for a variety of computer vision tasks.
